The integrated production–inventory–distribution–routing problem

The integration of production and distribution decisions presents a challenging problem for manufacturers trying to optimize their supply chain. At the planning level, the immediate goal is to coordinate production, inventory, and delivery to meet customer demand so that the corresponding costs are minimized. Achieving this goal provides the foundations for streamlining the logistics network and for integrating other operational and financial components of the system. In this paper, a model is presented that includes a single production facility, a set of customers with time varying demand, a finite planning horizon, and a fleet of vehicles for making the deliveries. Demand can be satisfied from either inventory held at the customer sites or from daily product distribution. In the most restrictive case, a vehicle routing problem must be solved for each time period. The decision to visit a customer on a particular day could be to restock inventory, meet that day’s demand or both. In a less restrictive case, the routing component of the model is replaced with an allocation component only. A procedure centering on reactive tabu search is developed for solving the full problem. After a solution is found, path relinking is applied to improve the results. A novel feature of the methodology is the use of an allocation model in the form of a mixed integer program to find good feasible solutions that serve as starting points for the tabu search. Lower bounds on the optimum are obtained by solving a modified version of the allocation model. Computational testing on a set of 90 benchmark instances with up to 200 customers and 20 time periods demonstrates the effectiveness of the approach. In all cases, improvements ranging from 10–20% were realized when compared to those obtained from an existing greedy randomized adaptive search procedure (GRASP). This often came at a three- to five-fold increase in runtime, however.     

Global optima for the Zhou–Rozvany problem

We consider the minimum compliance topology design problem with a volume constraint and discrete design variables. In particular, our interest is to provide global optimal designs to a challenging benchmark example proposed by Zhou and Rozvany. Global optimality is achieved by an implementation of a local branching method in which the subproblems are solved by a special purpose nonlinear branch-and-cut algorithm. The convergence rate of the branch-and-cut method is improved by strengthening the problem formulation with valid linear inequalities and variable fixing techniques. With the proposed algorithms, we find global optimal designs for several values on the available volume. These designs can be used to validate other methods and heuristics for the considered class of problems.     

A mixed hemivariational–variational problem and applications

We consider an abstract system with Lagrange multipliers which consists of a hemivariational inequality and a variational inequality. The hemivariational inequality is governed by a hemicontinuous, generalized monotone, possibly nonlinear operator as well as by a bilinear form. This bilinear form also governs the variational inequality. We are looking for a pair solution in a subset of a product of two real reflexive Banach spaces. In order to illustrate the applicability of the abstract results, two examples in terms of PDEs are delivered. Each example is related to the weak solvability of a boundary value problem arising in contact mechanics.     

First vorticity–velocity–pressure numerical scheme for the Stokes problem

We consider the bidimensional Stokes problem for incompressible fluids and recall the vorticity, velocity and pressure variational formulation, which was previously proposed by one of the authors, and allows very general boundary conditions. We develop a natural implementation of this numerical method and we describe in this paper the numerical results we obtain. Moreover, we prove that the low degree numerical scheme we use is stable for Dirichlet boundary conditions on the vorticity. Numerical results are in accordance with the theoretical ones. In the general case of unstructured meshes, a stability problem is present for Dirichlet boundary conditions on the velocity, exactly as in the stream function-vorticity formulation. Finally, we show on some examples that we observe numerical convergence for regular meshes or embedded ones for Dirichlet boundary conditions on the velocity.     

The multi-facility location–allocation problem with polyhedral barriers

In this paper we consider the problem of locating N new facilities with respect to M existing facilities in the plane and in the presence of polyhedral barriers. We assume that a barrier is a region where neither facility location nor traveling is permitted. For the resulting multi-dimensional mixed-integer optimization problem two different alternate location and allocation procedures are developed. Numerical examples show the superiority of a joint treatment of all assignment variables, including those specifying the routes taken around the barrier polyhedra, over a separate iterative solution of the assignment problem and the single-facility location problems in the presence of barriers.     

The Deutsch–Jozsa problem: de-quantisation and entanglement

The Deutsch–Jozsa problem is one of the most basic ways to demonstrate the power of quantum computation. Consider a Boolean function f : {0, 1} ⁿ → {0, 1} and suppose we have a black-box to compute f. The Deutsch–Jozsa problem is to determine if f is constant (i.e. f(x) = const, "x ? {0,1}ⁿf(x) = \hbox {const, } \forall x \in \{0,1\}^n) or if f is balanced (i.e. f(x) = 0 for exactly half the possible input strings x ? {0,1}ⁿx \in \{0,1\}^n) using as few calls to the black-box computing f as is possible, assuming f is guaranteed to be constant or balanced. Classically it appears that this requires at least 2 ⁿ⁻¹ + 1 black-box calls in the worst case, but the well known quantum solution solves the problem with probability one in exactly one black-box call. It has been found that in some cases the algorithm can be de-quantised into an equivalent classical, deterministic solution. We explore the ability to extend this de-quantisation to further cases, and examine with more detail when de-quantisation is possible, both with respect to the Deutsch–Jozsa problem, as well as in more general cases.     

Principal–agent problem: a cognitive map approach

As software agents become more and more intelligent, it becomes more and more difficult for human principals to understand and control them. This is a well-known principal–agent problem. There is, thus, need for a tool that can bridge the gap between human principals and software agents. In this paper, we discuss a new approach based on cognitive map to understand and control the knowledge of software agents. We propose a hierarchical framework to construct cognitive map from the rule base of software agents with the help of some guidelines. We applied the cognitive map approach to the famous Pursuit problem and demonstrated how learning can takes place with the help of cognitive maps. In this study, we found that cognitive map could be a promising tool for understanding and controlling intelligent software agents.     

The input–output version of the Aizerman–Myshkis problem for retarded systems

Non-linear retarded systems are considered. Conditions for the input-output stability are derived. They are formulated in terms of the zeros of the corresponding quasi-polynomials. In addition, it is proved that retarded systems with positive impulse (Green) functions satisfy the Aizerman-Myshkis conjecture in the input-output version.     

The role of co-explanation and self-explanation in learning from design examples of PowerPoint presentation slides

The current study investigated how people learn design principles from examples of PowerPoint presentation slides through self-explanation and co-explanation. This study also explored a strategy to improve the effectiveness of co-explanation by integrating it with a collaborative design activity. Preservice teachers (n = 120) studied the design examples of PowerPoint presentation slides in four research conditions: co-explanation with design, co-explanation, self-explanation, and no prompt (control). Pairs of learners in the co-explanation condition explained fewer strengths and weaknesses of the design examples than nominal pairs in the self-explanation condition. Moreover, co-explanation was not more effective than self-explanation when it came to individual learning outcomes. In contrast, pairs in the co-explanation with design condition were more actively engaged in co-explaining design examples than pairs in the co-explanation condition. This study shows that co-explanation with design is more beneficial for constructing and sharing knowledge of design principles than co-explanation only. This study discussed a trade-off between constructive/interactive learning effects and transactional activity costs in co-explaining design examples.     

Acquisition of troubleshooting skills in a computer simulation: Worked example vs. conventional problem solving instructional strategies

In a computer-based simulation of a chemical processing plant, the differential effects of three instructional strategies for learning how to troubleshoot the plant’s malfunctions were investigated. In an experiment concerning learners’ transfer performance and mental effort, the simulation presented the three strategies to three groups of learners and measured their performance on the transfer tasks. In this experiment, conventional problem solving was contrasted with two worked example strategies. The results indicated a significant difference between practicing problem solving and using worked examples. Learners who practiced problem solving in an interactive simulation outperformed the learners who studied computer-based worked examples. They also invested lower mental effort in transfer tasks. When accounting for the difference in the learners’ domain knowledge, the strategies were not significantly different among the more experienced learners. For the less experienced learners, those who practiced problem solving significantly outperformed their worked example counterparts. Among all participants and also among less experienced learners the problem solving group invested significantly lower mental effort in the performance of transfer tasks. Based on the results of this study, the authors recommend the use of the conventional problem solving strategy with or without worked examples for learning complex skills.     

Computer-supported example-based learning: When instructional explanations reduce self-explanations

We investigated whether the findings from worked-out example research on the effects of self-explanation prompts and on instructional explanations can be generalized to other example types – in this case: solved example problems. Whereas worked-out examples consist of a problem formulation, solution steps, and the final solution, solved example problems merely provide the problem formulation and the solution. We employed a first module of a computer-based environment for student teachers presenting solved example problems from which they learned how to select and to design worked-out examples for high school students. The participants (47 student teachers for German low- and medium-track schools and 33 student teachers for high-track schools) were randomly assigned to the cells of our 2 × 2 design (with vs. without self-explanation prompts; with vs. without instructional explanations). The effects of the different program versions on objective and subjective learning outcomes, on the perceived helpfulness of the program, and on the learning time were analyzed. As learning process data, the written and spoken self-explanations were assessed. The following main results were obtained: Particularly self-explanation prompts had favorable effects on learning outcomes, whereas instructional explanations can reduce the student teacher’s self-explanation activities and thereby the learning outcomes. Whereas “objectively” the most favorable learning outcomes were obtained when only self-explanation prompts were employed, the student teachers perceived their learning outcome best when only instructional explanations were provided. It can be concluded that the status of self-explanation prompts and of instructional explanations is comparable irrespective of the example type presented for learning.     

Using eye movement modelling examples to guide visual attention and foster cognitive performance: A meta-analysis

Eye movement modelling examples (EMME) are computer-based videos displaying the visualized eye gaze behaviour of a domain expert person (model) while carefully executing the learning or problem-solving task. The role of EMME in promoting cognitive performance (i.e., final scores of learning outcome or problem solving) has been questioned due to the mixed findings from empirical studies. This study tested the effects of EMME on attention guidance and cognitive performance by means of meta-analytic procedures. Data for both experimental and control groups and both posttest and pretest were extracted to calculate the effect sizes. The EMME group was treated as the experimental group and the non-EMME group was treated as the control group. Twenty-five independent articles were included. The overall analysis showed a significant effect of EMME on time to first fixation (d = −0.83), fixation duration (d = 0.74), as well as cognitive performance (d = 0.43), but not on fixation count, indicating that using EMME not only helped learners attend faster and longer to the task-relevant elements, but also fostered their final cognitive performance. Interestingly, task type significantly moderated the effect of EMME on cognitive performance. Moderation analyses showed that EMME was beneficial to learners' performance when non-procedural tasks (rather than procedural tasks) were used. These findings show contributions for future research as well as practical application in the field of computers and learning regarding videos displaying a model's visualized eye gaze behaviour.     

Students’ perceptions of creativity in learning Information Technology (IT) in project groups

This paper explores students’ perceptions of creativity in learning Information Technology (IT) in project groups and the implications of better educating creative IT students for the future. Theoretically, the extension of social psychology research into creativity lays the basis of bringing creativity, learning and IT education into one framework. Empirically, qualitative interviews were carried out with 48 students from three disciplines, including Computer Science (n = 16), Electronic Systems (n = 15) and Medialogy (n = 17) at Aalborg University (AAU) in Denmark, which has a tradition of using problem-based learning (PBL) in student project groups. According to the findings, the students’ perceptions of creativity reflect their domain-related conceptualization and tacit learning experience, with different levels of confidence of being creative persons. As IT plays multiple roles in developing students’ creativity, it can be regarded as a ‘learning partner’. This implies that in the future creativity should be taught more explicitly, helping students to become creative IT talents as a part of their professional identity. It also requires teaching efforts to build a learning environment that stimulates creativity more effectively through more interactions between learners, learning tasks and learning tools.     

Learning with intelligent tutors and worked examples: selecting learning activities adaptively leads to better learning outcomes than a fixed curriculum

The main learning activity provided by intelligent tutoring systems is problem solving, although several recent projects investigated the effectiveness of combining problem solving with worked examples. Previous research has shown that learning from examples is an effective learning strategy, especially for novice learners. A worked example provides step-by-step explanations of how a problem is solved. Many studies have compared learning from examples to unsupported problem solving, and suggested presenting worked examples to students in the initial stages of learning, followed by problem solving once students have acquired enough knowledge. This paper presents a study in which we compare a fixed sequence of alternating worked examples and tutored problem solving with a strategy that adapts learning tasks to students’ needs. The adaptive strategy determines the type of the task (a worked example, a faded example or a problem to be solved) based on how much assistance the student received on the previous problem. The results show that students in the adaptive condition learnt significantly more than their peers who were presented with a fixed sequence of worked examples and problem solving. Novices from the adaptive condition learnt faster than novices from the control group, while the advanced students from the adaptive condition learnt more than their peers from the control group.     

Is workplace satisfaction associated with self-reported quad bike loss of control events among farm workers in New Zealand?

This study investigated whether rural workers who have higher workplace satisfaction are less likely to report quad bike loss of control events (LCEs). Two independent samples of farmers completed a survey regarding LCEs and workplace satisfaction. In the first sample (n = 130) analysis revealed no relationship (p = 0.74) between workplace satisfaction and LCEs but lower rates of LCEs were reported by employees (IRR 0.52, 95%CI 0.31–0.86) compared to self-employed participants. In the second sample (n = 112), workplace satisfaction was weakly related to LCEs (IRR 1.04, 95%CI 1.00, to 1.09) with participants who found their job more psychologically demanding more likely to have had an LCE (IRR 1.14, 95%CI 1.05–1.23). Exploring the role of psychological demands on safety behaviour with respect to quad bike use, may help to address this important safety issue.     

Constructing and evaluating online goal-setting mechanisms in web-based portfolio assessment system for facilitating self-regulated learning

The purpose of the present study was to construct goal-setting mechanisms in a web-based portfolio assessment system (WBPAS), based on the self-regulated learning (SRL) process proposed by Zimmerman, and to examine effects of these mechanisms on SRL. The participants were two classes of 11th graders taking the website design class in a vocational high school. The participants were assigned randomly to either an experimental group (n = 40) learning with a WBPAS or a control group (n = 41) learning with a paper-based portfolio. The study results revealed the following: a) the quality of goal-setting mechanisms may facilitate SRL. b) Students setting learning goals with the WBPAS demonstrated significantly better SRL than students setting learning goals with the paper-based portfolio.     

Showing a model's eye movements in examples does not improve learning of problem-solving tasks

Eye movement modeling examples (EMME) are demonstrations of a computer-based task by a human model (e.g., a teacher), with the model's eye movements superimposed on the task to guide learners' attention. EMME have been shown to enhance learning of perceptual classification tasks; however, it is an open question whether EMME would also improve learning of procedural problem-solving tasks. We investigated this question in two experiments. In Experiment 1 (72 university students, M_age = 19.94), the effectiveness of EMME for learning simple geometry problems was addressed, in which the eye movements cued the underlying principle for calculating an angle. The only significant difference between the EMME and a no eye movement control condition was that participants in the EMME condition required less time for solving the transfer test problems. In Experiment 2 (68 university students, M_age = 21.12), we investigated the effectiveness of EMME for more complex geometry problems. Again, we found no significant effects on performance except for time spent on transfer test problems, although it was now in the opposite direction: participants who had studied EMME took longer to solve those items. These findings suggest that EMME may not be more effective than regular video examples for teaching procedural problem-solving skills.     

Adaptive diagrams: Handing control over to the learner to manage split-attention online

Based on cognitive load theory, it is well known that when studying a diagram that includes explanatory text, optimal learning occurs when the text is physically positioned close to the diagram as it eliminates the need for learners to split their attention between the two sources of information. What is not known is the effect on learning when learners manage split-attention for themselves when presented with a separated diagram and explanatory text. This study focuses on this new research direction by examining how learners can self-manage cognitive load through the physical manipulation of digital materials. Physical manipulation refers to moving text objects in digital materials to connect related pieces of textual information to a diagram, thus adapting the diagram to reduce split-attention. Fifty-two university students participated in one of two experiments. Experiment 1 (N = 34) investigated whether learners who were guided to self-manage split-attention by moving text objects on a screen displaying instructional material with evident split-attention were able to reduce split-attention and thus outperform learners who were provided split-source materials. Experiment 2 (N = 18) collected verbal think-aloud protocols to uncover the students' learning processes with the materials. Results confirmed the split-attention effect thus replicating this effect in a digital domain. Furthermore, whilst the self-managed condition did not significantly outperform the split-attention condition, the added task for learners to move text boxes to relevant aspects of the diagram did not have an adverse effect on learning, as the self-managed condition performed as well as (and for a recall task slightly better than) the split-attention condition. The verbal protocols highlighted that in order for learners to successfully self-manage split-attention training and guidance needs to be more extensive and explicit. Implications for further research for this new research direction in cognitive load theory are discussed.